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European Journal of Forest Research

, Volume 126, Issue 2, pp 263–270 | Cite as

Allometric equations for estimating the foliage biomass of Scots pine

  • Jarosław SochaEmail author
  • Piotr Wezyk
Original Paper

Abstract

The research described in this paper was performed in the Niepolomice Forest (Southern Poland) in 2001 as part of the Forest Environmental Monitoring and Management System (FOREMMS; 5FP IST) project. The material for the present study consisted of the measurement results of the biomass of Scots pine shoots with needles and needles alone carried out on 113 felled sample trees. The purpose of this study was to construct empirical equations for estimating the foliage biomass of Scots pine from easy to measure parameters. To achieve this aim, the dependence of the foliage biomass of Scots pine on stem diameter, height, age, crown length, basal area increment of the trees was analyzed. Using the biometric characteristics such as: tree diameter at breast height (dbh), basal area increment, age, height, and crown length empirical equations for estimating the foliage biomass of Scots pine reasonably precisely have been established. The created empirical equation gives accurate foliage biomass estimates. The explained variability varies between 65 and 85%, it depends on the number of variables applied in the equation. The equations presented in this paper were created with a view to their possible use in ecological studies where biomass quantity may be used, for example, in modeling carbon circulation in the forest ecosystem. From the point of view of forestry practice, these equations may help to assess biomass production in Scots pine stands.

Keywords

Foliage biomass Allometric equations Pinus sylvestris L. 

References

  1. Altman DG (1991) Practical statistics for medical research. Chapman and Hall, LondonGoogle Scholar
  2. Baker TG, Attiwill PM, Stewart HTL (1984) Biomass equations for Pinus radiata in Gippsland, Victoria. NZ J For Sci 14(1):89–96Google Scholar
  3. Baldwin VC, Peterson KD, Burkhatt HE, Amateis RL, Doughtery PM (1997) Equations for estimating loblolly pine branch and foliage weight and surface area distributions. Can J For Res 27:918–927CrossRefGoogle Scholar
  4. Barcikowski A, Loro PM (1995) Needle biomass and dendrometrical features of Scots pine (Pinus sylvestris L.) natural regeneration seedlings of younger age classes, growing on a fresh coniferous forest site. Sylwan 139(2):53–62Google Scholar
  5. Baskerville GL (1972) Use of logarithmic regression in the estimation of plant biomass. Can J For Res 2:49–53CrossRefGoogle Scholar
  6. Burger H (1929) Holz, Blattmenge und Zuwachs. I: Die Weymouthsföhre. Mitt Schw Anst Forstl Versw 15:243–292Google Scholar
  7. Burger H (1945) Holz, Blattmenge und Zuwachs. VII: Die Larche. Mitt Schw Anst Forstl Versw 24:7–103Google Scholar
  8. Burger H (1953) Holz, Blattmenge und Zuwachs. XIII: Fichten im gleichaltrigen Hochwald. Mitt Schw Anst Forstl Versw 29:38–103Google Scholar
  9. Claesson S, Sahlén K, Lundmark T (2001) Functions for biomass estimation of Young Pinus sylvestris, Picea abies and Betula spp. from stands in Northern Sweden with high stand densities. Scand J For Res (16)2:138–146Google Scholar
  10. Chroust L (1985) Above ground biomass of young pine forest (Pinus sylvestris) and its determination. Commun Inst Forestalis Cechosloweniae 14:127–145Google Scholar
  11. De los Santos-Posadas H, Borders BE (2002) Empirical allometric models to estimate total needle biomass for loblolly pine. In: Proceedings of the 11th biennial southern silvicultural research conference. USDA-FS. General Technical Report SRS, pp 431–437Google Scholar
  12. Eliott KJ, Clinton BD (1993) Equations for estimating biomass of herbaceous and woody vegetation early-successional southern Appalachian pine-hardwood forests. USDA Forest Service. Research Note SE-365Google Scholar
  13. Fox J (1991) Regression diagnostics: an introduction. Sage university paper series on quantitative applications in the social sciences, Sage, Newbury Park p7–79Google Scholar
  14. Goulden ML, Munger JW, Fan S-M, Daube BC, Wofsy SC (1996) Exchange of carbon dioxide by a deciduous forest: response to interannual climate variability. Science 271:1576–1578Google Scholar
  15. Grace JC, Jarvis PG, Norman JM (1987) Modelling the interception of solar radiant energy in intensively managed stands. N Z J For Sci 17:119–203Google Scholar
  16. Gregoire TG, Valentine HT, George M, Furnival GM (1995) Sampling methods to estimate foliage and other characteristics of individual trees. Ecology 4:1181–1194Google Scholar
  17. Grote R (2002) Foliage branch biomass estimation of coniferous and deciduous tree species. Silva Fenn 36(4):779–788CrossRefGoogle Scholar
  18. Hoffmann CW, Usoltsev VA (2002) Tree-crown biomass estimation in forest species of the Ural and Kazakhstan. For Ecol Manage 158:59–69CrossRefGoogle Scholar
  19. Hooker TD, Compton JE (2003) Forest ecosystem carbon and nitrogen accumulation during the first century after agricultural abandonment. Ecol Appl 2:299–313Google Scholar
  20. Heinsdorf D, Krauß H-H (1990) Schätztafeln für Trockenmasse und Nährstoffspeicherung von Kiefernbeständen. IFE-Ber Forsch Entwickl 18:77Google Scholar
  21. Helmisari HS, Makkonen K, Kellomaki S, Valtonen E, Malkonen E (2002). Below- and above- ground biomass, production and nitrogen use in Scots pine stands in eastern Finland. For Ecol Manage 165:317–326Google Scholar
  22. Koerper GJ, Richardson CJ (1980) Biomass and net annual primary production regressions for Populus grandientata on three sites in northern lower Michigan. Can J For Res 10:92–101CrossRefGoogle Scholar
  23. Lehtonen A (2005) Estimating foliage biomass in Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) plots. Tree Physiol 25:803–811CrossRefPubMedGoogle Scholar
  24. Lemke J (1968) Związek pomiędzy wielkością korony a przyrostem drzew w drzewostanach sosnowych. The dependence of the crown size and tree increment in the Pine stands. PTPN, t. XXV:1–48Google Scholar
  25. Lemke J (1975) Szacowanie ciężaru świeżego igliwia sosny zwyczajnej. Estimation of the foliage biomass of Scots Pine. Sylwan 6:37–44Google Scholar
  26. Lemke J (1983) Tables for estimation of the weight of needles and twigs with needles of the Scots pine. Sylwan 2:21–30Google Scholar
  27. Lemke J, Wozniak A (1992) Szacowanie masy 1-, 2-, 3-letniego igliwia sosen roznych klas wieku. Estimation of 1-, 2-, 3-age foliage biomass of different age class. Sylwan 9:25–32Google Scholar
  28. Lemke J, Kazmierczak K, (1993) Zależność między aparatem asymilacyjnym a niektórymi rodzajami przyrostów drzew w drzewostanach sosnowych. The dependence of the foliage biomass on the tree increment in Pine stands. PTPN, t. LXXVI, 73–78Google Scholar
  29. Mäkelä A, Vanninen P (1998) Impact size and competition on tree form and distribution of aboveground biomass in Scots Pine. Can J For Res 28:216–227CrossRefGoogle Scholar
  30. McCray RL, Joel EJ (1998) Canopy dynamics, light interception, and radiation use efficiency of selected loblolly pine families. For Sci 44:64–72Google Scholar
  31. Monserud RA, Marshall JD (1999) Allometric crown relations in three northern Idaho conifer species. Can J For Res 29:521–535CrossRefGoogle Scholar
  32. Monserud RA, Onuchin A, Chebakova N (1996) Needle, crown, stem, and root phytomass of Pinus silvestris stands in Russia. For Ecol Manage 82:59–67Google Scholar
  33. Oleksyn J, Reich PB, Chalupka W, Tjoelker MG (1999) Differential above- and belove-ground biomass accumulation of European Pinus sylvestris populations in a 12-year-old provenance experiment. Scand J For Res 14:7–17CrossRefGoogle Scholar
  34. Santa Regina I, Tarazona T (2001) Nutrient cycling in a natural beech forest and adjacent planted pine in northern Spain. Forestry 74:11–28Google Scholar
  35. Shinozaki K, Yoda K, Hozumi K, Kira T (1964) A quantitative analysis of plant forms. The pipe model theory. I. Basic analyses. Jpn J Ecol 14:133–139Google Scholar
  36. Sit V, Poulin-Costello M (1994) Catalogue of curves for curve fitting. Biometrics information handbook series, no. 4. Ministry of Forests Province of British Columbia, Vic., AustraliaGoogle Scholar
  37. Socha J, Wezyk P (2004) Empirical formulae to assess the biomass of the above-ground part of pine trees. El J Pol Agric Univ For 7(2). http://www.ejpau.media.pl/volume7/issue2/forestry/art-04.html04.html
  38. StatSoft Inc (2004) STATISTICA (data analysis software system), version 6. http://www.statsoft.com
  39. Temesgen H, Gadow Kv (2004) Generalized height-diameter models-an application for major tree species in complex stands of interior British Columbia. Eur J For Res 123:45–51Google Scholar
  40. Vanninen P, Ylitalo H, Sievänen R, Mäkaelä A (1996) Effects of age and site quality on the distribution of biomass in Scots pine (Pinus sylvestris L.). Trees 10:231–238Google Scholar
  41. Wezyk P, Koziol K, Madejczyk A (2001) Zakładanie sieci powierzchni monitoringowych w terenach leśnych metoda DGPS. I Krajowa Konferencja System Informacji Przestrzennej w Lasach Państwowych—Rogow. http://www.lasypanstwowe.gov.pl/sip. [Establishing of the monitoring grids on the forest areas using the DGPS method. First National Conference GIS in the Polish State Forest National Holding, Rogow]Google Scholar
  42. Wezyk P (2004) Integracja technologii geoinformatycznych w systemie monitoringu i zarzadzania ekosystemami lesnym Europy, na przykladzie projektu FOREMMS (5 PR UE). W: Teledetekcja Srodowiska. Warszawa 33:75–81. [Integration of geoinformation technologies in system designed for monitoring and management of European forest ecosystems, based on example of FOREMMS project (5FP IST)]Google Scholar
  43. Xiao CW, Curiel Yuste J, Janssens IA, Roskams P, Nachtergale L, Carrara A, Sanchez BY, Ceulemans R (2003) Above- and belowground biomass and net primary production in a 73-year-old Scots pine forest. Tree Physiol 23:505–516Google Scholar
  44. Xu M, Harrington TB (1998) Leaf biomass distribution of loblolly pine as affected by tree dominance, crown size, and stand characteristics. Can J For Res 28:887–892Google Scholar
  45. Zianis D, Menuccini M (2003) Aboveground biomass relationships for beech (Fagus moesiaca Cz.) trees in Vermio Mountain, Northern Greece, and generalised equations for Fagus sp. Ann For Sci 60:439–448 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Department of Forest Mensuration, Faculty of ForestryAgricultural University of CracowCracowPoland
  2. 2.Department of Forest Ecology, Laboratory of GIS and RS, Faculty of ForestryAgricultural University of CracowCracowPoland

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